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How can we help you?
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Marija Mijic
HR & Office Allrounder
T +43 660 383 95 46
office@craftworks.at
craftworks GmbH
Schottenfeldgasse 20/6a
1070 Vienna
Energy Saving through
Process Optimization
We created an AI based controlling software for a multinational performance coatings producer.
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Success Story
reading time: 2 min
Automotive
Material Industries
Predictive Quality
Predictive Maintenance
Industrial Software
20%
Reduction in energy use
Accurate
Identification of press time duration
Lower
Carbon footprint
Context
The producer wanted to create intelligent solutions for their customers that use radio frequency press for wood adhesives.
Challenge
The press time it would take to adhere wooden parts, varied based on their experience, but the optimal time highly depended on the material’s properties (wood and glue). The hypothesis stated that changes in the voltage curve, used during the RF (radiofrequency), could indicate the optimal end of the process.
Assignment
Our task was to determine the optimal press time based on parameters of the RF (radio frequency) press. There were two important considerations:
1. Leveraging process data in real-time to detect when the optimal press time had been reached.
2. Predicting the optimal press time based on specific conditions.
Solution
We applied this algorithm to the historic data to find all the optimal press durations and trained a machine learning model to predict this duration based on the available information at the start of the process: material properties, dimensions, etc.
We implemented a signal-processing algorithm to detect the ideal stopping point of press time, which can be used in real time.
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